Novel manifestations of Warburg micro syndrome type 1 caused by a new splicing variant of RAB3GAP1: a case report
Bibliographic record
Abstract
BACKGROUND: The present study aimed to determine the underlying genetic factors causing the possible Warburg micro syndrome (WARBM) phenotype in two Iranian patients. CASE PRESENTATION: A 5-year-old female and a 4.5-year-old male were referred due to microcephaly, global developmental delay, and dysmorphic features. After doing neuroimaging and clinical examinations, due to the heterogeneity of neurodevelopmental disorders, we subjected 7 family members to whole-exome sequencing. Three candidate variants were confirmed by Sanger sequencing and allele frequency of each variant was also determined in 300 healthy ethnically matched people using the tetra-primer amplification refractory mutation system-PCR and PCR-restriction fragment length polymorphism. To show the splicing effects, reverse transcription-PCR (RT-PCR) and RT-qPCR were performed, followed by Sanger sequencing. A novel homozygous variant-NM_012233.2: c.151-5 T > G; p.(Gly51IlefsTer15)-in the RAB3GAP1 gene was identified as the most likely disease-causing variant. RT-PCR/RT-qPCR showed that this variant can activate a cryptic site of splicing in intron 3, changing the splicing and gene expression processes. We also identified some novel manifestations in association with WARBM type 1 to touch upon abnormal philtrum, prominent antitragus, downturned corners of the mouth, malaligned teeth, scrotal hypoplasia, low anterior hairline, hypertrichosis of upper back, spastic diplegia to quadriplegia, and cerebral white matter signal changes. CONCLUSIONS: Due to the common phenotypes between WARBMs and Martsolf syndrome (MIM: 212720), we suggest using the "RABopathies" term that can in turn cover a broad range of manifestations. This study can per se increase the genotype-phenotype spectrum of WARBM type 1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".